Our curriculum combines coursework in bioinformatic computational methods, programming, and statistics with graduate electives that offer students the flexibility to specialize and build broader knowledge in both life sciences and computer sciences.
Required Core (20 semester hours):
BIOL6308 Bioinformatics Computational Methods 1 (4 SH) – semester 1
BIOL6309 Bioinformatics Computational Methods 2 (4 SH) – semester 2
BIOL6200 Bioinformatics Programming (4 SH) – semester 3
MATH7340 Statistics for Bioinformatics (4 SH) – year 1
BIOL7385 Bioinformatics Seminar (2 SH) – take at least once
BIOL6381 Ethics in Biological Research (2 SH) – year 1
Electives (12 semester hours):
Students take a diverse array of graduate electives in biology, chemistry, math, and computer science depending on their background and strengths. Popular electives include:
Molecular Modeling (CHEM5638)
Database Management (CS5200)
Molecular Cell Biology (BIOL6301)
Web Development (CS5610)
The required 3 – 6 month co-op can be started any time after the completion of 16 credits of graduate coursework.
Bioinformatics Computational Methods 1 (4 SH)
Offers the first semester of a two-semester sequence on the use of computers in bioinformatics research. Offers students an opportunity to work with current methods and computational algorithms used in contemporary sequence analysis. Teaches practical skills necessary to manage and mine the vast biological information being generated and housed in public databases. Emphasizes the use of Perl as the primary computer language and requires students to learn and understand basic computer logic and syntax, including an introduction to scalars, arrays, hashes, decision statements, loops, subroutines, references, and regular expressions. A focus on fundamental skills, including the command line interface found in the Linux operating system, is designed to prepare students for second-semester applications.
Bioinformatics Computational Methods 2 (4 SH)
Designed to build upon the core topics covered in BIOL 6308, i.e., use of the computer as a tool for bioinformatics research. Builds upon the Perl language fundamentals covered during the first semester but requires students to apply these fundamentals to a semester-long project. The project includes protein family analysis, multiple sequence analysis, phylogeny, and protein structure analysis. Additionally, students have an opportunity to learn to build, load, connect, and query custom MySQL databases, parse command line flags, and build Perl objects. Prereq. BIOL 6308.
Bioinformatics Programming (4 SH)
Surveys programming techniques using examples and exercises from bioinformatics. Python is the main programming language used, and the course ends with a brief introduction to Perl. Topics include string operations, file manipulations, regular expressions, object-oriented programming, database access, and an introduction to the BioPython/BioPerl libraries. Substantial out-of-classroom assignments are an essential instructional component. Most students have had at least some prior programming experience, but that is not a requirement.
Statistics for Bioinformatics (4 SH)
Introduces the concepts of probability and statistics and the statistical concepts used in genomics (sequence alignment algorithms, mapping gene, and protein stochastic networks) and in drug discovery and evaluation. Methods include theoretical approaches such as maximum likelihood, entropy maximization, minimal description length, and empirical methods based on clustering, pattern recognition, bootstrapping, neural networks, Markov chain Monte Carlo, fitting Markov models of local interactions, and Bayesian models. Discusses application examples of discriminant analysis, principal components, multiple correlation, regression, and design of experiments to bioinformatics.Prereq. Bioinformatics majors only.
Bioinformatics Seminar (2 SH)
Discusses current issues and research topics in bioinformatics. Requires student presentations. Prereq. Biology students only.
Ethics in Biological Research (2 SH)
Discusses ethical issues relevant to research in the biological sciences. Requires student presentations.